code: def _execute_shuffle_reduce(cls, ctx, op: "DataFrameDuplicated"):
      out = op.outputs[0]
      inputs = list(op.iter_mapper_data(ctx))
  
      xdf = cls._get_xdf(inputs[0])
      inp = xdf.concat(inputs)
      subset = [
          c for c in inp.columns if c not in ("_chunk_index_", "_i_")
      ]
      duplicated = cls._duplicated(inp, op, subset=subset)
      result = xdf.concat(
          [duplicated, inp[["_chunk_index_", "_i_"]]], axis=1
      )
      for i in range(op.shuffle_size):
          filtered = result[result["_chunk_index_"] == i]
          del filtered["_chunk_index_"]
          if len(subset) > 1 or subset[0] == "_duplicated_":
              filtered.columns = ["_duplicated_"] + filtered.columns[
                  1:
              ].tolist()
          else:
              filtered.columns = [subset[0]] + filtered.columns[
                  1:
              ].tolist()
          ctx[out.key, (i,)] = filtered
  
imports: import numpy
  from ...None import opcodes
  from ...core import OutputType
  from ...core.operand import OperandStage
  from ..utils import gen_unknown_index_value, hash_dataframe_on
  from ._duplicate import DuplicateOperand, validate_subset
label_desc: Use image node_id 17 for calling the DataFrameDuplicated obj's underlying member method code with example usage: obj._execute_shuffle_reduce(cls, ctx, op) without return types